Skip to content
The Kim and Don Richards Family Foundation at a glanceAlso receives grants: funding profile →

· Private foundation

The Kim and Don Richards Family Foundation

Its FY2025 filing reports that it funds preselected organizations and did not take unsolicited requests; check the foundation's own site before ruling it out.

$4k
Granted FY2020
7
Grants FY2020
2
States reached
$3k
Largest
01What it fundsRead
02The needRead
03Its fieldRead
01What it funds
0181% classified

What it funded, over time

Every grant placed by its stated purpose and the recipient’s mission, by year, FY2017 to 2020.

Public Safety & Disaster$17kRecreation & Sports$625Animals$350Housing & Shelter$250Arts & Culture$50Health$50Human Services$20Philanthropy$20Other$0
02FY2020 · 7 grants

Where the money goes

Grants by size, and the largest recipients.

$250
Median grant
2
States reached
$1k
Total assets
Largest grants
RecipientAmount
HOUSTON POLICE FOUNDATION$3,000
Individual grant recipient$500
TEXAS WOLFDOG PROJECT$300
HARRY'S HOME$250
NSWCC$100
Individual grant recipient$100
ATHLETES WITHOUT LIMITS$75
02The need
03

Does the money reach high-need areas?

Each grant placed by the hardship in its grantee’s ZIP, against the area’s typical level.

show:

Its human-services grants (FY17–20, $17k) land where the poverty rate runs at 16%, against an area that typically sits at 11%. 100% of those dollars go to grantees based in above-average-need neighborhoods. Most of its grants land in higher-need ZIPs.

area typical 11%ATHLETES WITHOUT LIMITS: $75 → 10%HOUSTON POLICE FOUNDATION: $9k → 16%HOUSTON POLICE FOUNDATION: $5k → 16%HOUSTON POLICE FOUNDATION: $3k → 16%0%20%40%50%more need →
grant to an above-average-need area below average· circle size = grant amount
How this is measured
Matched: human-services grants are those whose grantee’s IRS cause code is Human Services. Placed by people below the poverty line in the grantee’s ZIP, averaged from the tracts in that ZIP.
How this is measured
US grants placed by each grantee’s ZIP, which can differ from where services are delivered. Need from public data (U.S. Census/ACS, CDC PLACES, Eviction Lab, USDA), shown as context about the area, never attributed to the funder’s giving.
03Its field

Closest unfunded matches

The nonprofits that most resemble its grantees but are not funded by it, scored along the direction from the rest of the field toward the portfolio. A resemblance in what they say they do, not a recommendation.

1
Wings of Hope Therapeutic Riding Program Inc
—
2
Veteran Equine Therapy Stables
Public Benefit
3
Freedom Hooves Therapeutic Riding of Nw Colorado
—
4
Great Results Equine Assisted Therapies
Health
5
Woodland Strides
Health
6
Hollie Brewer Adaptive Rodeo Inc
Recreation & Sports
7
Heroes Equine Assisted Riding Therapy
—
8
Therapeutic Riding Institute Inc

To improve the lives and health of children and adults in southwest Ohio with special physical, cognitive, social and psychological needs through equine assisted services and therapies. TRI partners extensively with community organizations…

—
9
Impact Horse- Connecting Humans and Horses
Animals
10
Equus Rescue and Therapy Inc

Rescue rehabilitation recovery of equine mammals

Animals
11
Blue Horse Sanctuary
Animals
12
Therapeutic Riding and Off-Track Rehabilitation Trotr

The rehabilitation of horses and people through interaction with each other.

Animals
How this is measured
The grantee most central to the portfolio’s shape is Special Olympics of Texas Inc; the most unlike its peers is Reining Strength Therapeutic Horsemanship. Resemblance is measured on each organization’s own IRS 990 mission text; it reflects how work is described, not its quality or impact.
04the grantee network

9 grantees tracked through their own filings, 2017–2025.

Each grant beside the grantee’s revenue from every source, year by year.

How this is measured

Counted here: distinct organizations funded across 2017 to 2025, not grant rows in a single year, so this will not match the grant count on the cover. 9 of the 14 grantees resolved in that span have returns of their own we could reconcile.

Each grantee is resolved to its own IRS returns. Association, dated; never a causal claim.

0
Load-bearing (≥25% of a budget)
4
Early backer (in before they grew)
9/9
Grantees still filing
7/9
Grew since first funded

Where the money sits, by cause and then by grantee

HOUSTON POLICE FOUNDATION: $17,000 · Human ServicesHOUSTON POLICE FOUNDATION+1 more: $75 · Human ServicesIndividual grant recipient: $500 · OtherHARRY'S HOME: $250 · OtherIndividual grant recipient: $100 · OtherNSWCC: $100 · OtherSIRE INC: $50 · OtherREINING STRENGTH THERAPEUTIC HORSEMANSHIP: $50 · Other+1 more: $20 · OtherSPECIAL OLYMPICS OF TEXAS INC: $500 · Recreation & SportsTEXAS WOLFDOG PROJECT: $300 · AnimalsHenrys Home Horse and Human Sanctuary: $50 · AnimalsHISTORIC LANSDOWNE THEATER CORP: $50 · Arts & CultureNETWORK FOR GOOD: $20 · Public Safety & Disaster
Human Services$17,075Other$1,070Recreation & Sports$500Animals$350Arts & Culture$50Public Safety & Disaster$20

Each grantee by its size and the funder’s share of it; top left is load-bearing

25%50%75%100%$1.0M$10M$100Mgrantee revenue →↑ funder's share of their budgetHOUSTON POLICE FOUNDATION: $17,000 over 3y, 0.2% of budgetSPECIAL OLYMPICS OF TEXAS INC: $500 over 1y, 0.0% of budgetTEXAS WOLFDOG PROJECT: $300 over 1y, 0.4% of budgetATHLETES WITHOUT LIMITS: $75 over 1y, 0.1% of budgetHenrys Home Horse and Human Sanctuary: $50 over 1y, 0.0% of budgetSIRE INC: $50 over 1y, 0.0% of budgetREINING STRENGTH THERAPEUTIC HORSEMANSHIP: $50 over 1y, 0.0% of budgetHISTORIC LANSDOWNE THEATER CORP: $50 over 1y, 0.0% of budgetNETWORK FOR GOOD: $20 over 1y, 0.0% of budget
Grantee by grantee: a decade per organization, before and after funding

A decade per grantee: revenue shaded, grants as bars, all rows on one timeline.

Co-funders

Grantmakers whose grantees overlap with this funder’s far more than size alone predicts. Closer means stronger alignment; arcs show where they also fund each other. Here they form a tightly interlocked group: most of these funders back each other's grantees too.

Shell USA Company Fou…American Online Givin…Fidelity Investments …Amazonsmile Foundation
Shell USA Company FoundationTX12.3× affinity4 shared granteesties to 3 of 3Hover any node to trace its alignments.Compare side by side →

Open a dossier: Shell USA Company Foundation · American Online Giving Foundation Inc · Fidelity Investments Charitable Gift Fund · Amazonsmile Foundation

How this is measured
Affinity is a Gamma-Poisson posterior co-funding rate, re-centered on the typical rate, so thin evidence shrinks toward no signal. Overlap is association, not proof of shared intent.

How much its grantees rely on government

Each dot is one organization The Kim and Don Richards Family Foundation funds: left to right is the share of its income from government, bottom to top the share from The Kim and Don Richards Family Foundation. Bigger dots raise more.

2024
’20’21’22’23’24
no gov · 10%0%1%3%5%funder's share of their income ↑0%25%50%75%100%share of the org’s income from government →
    no gov moneyreceives it· size = income
    1get no government money at all
    2report government grants on their 990 we could not trace to a source (not plotted)
    0rely on government for over half their income
    typical government reliance, FY20–24
    How this is measured
    Government income is each org’s traced federal awards (USASpending grants and contracts) plus state payments (open checkbooks) as a share of its total revenue (IRS Form 990); the self-reported government-grant line (990 line 1e) is carried for cross-check: a grantee that reports government grants we could not trace to a source is left off the chart rather than shown as receiving none. An association, not a claim that a grant caused the public funding. Coverage is precision-first, a floor rather than a census; state records exist for 9 states, so a grantee outside them shows no state figure (dimmed) rather than a false zero. Federal award amounts are obligations, which can span years, so a single-year share is indicative. 990 filings lag 12 to 24 months.

    On method. Every financial figure here is read from IRS e-file XML, the funder’s own 990/990-PF, and from the multi-year returns of the 14 grantees we resolved, each linked to its source. Grantee outcomes are each organization’s own program-service reporting (Form 990, Part III), read as association with funding, never as caused by it. Low-confidence name matches are suppressed rather than guessed. How we build these →

    How this is measured
    Each figure carries one of six labels. Filed is what the funder reported on its return. Official is another government record about an organization, such as a federal award or a charity register, joined by name where no shared identifier exists. Resolved is an identity we worked out where the filing named a recipient without an EIN, kept only above a measured confidence threshold. Computed is arithmetic over those, like themes, portfolio clusters and co-funder strength. Context is a statistic about a place rather than about an organization, which is what the need overlay is: it describes the area a grantee’s address sits in, not where its work lands. Inferred is drawn by a model from text, like the partnerships read out of public news and organization websites. Each is labeled where it appears.

    Generated from the IRS Form 990-PF e-file return for fiscal year 2020, released 2020. Filings run roughly 12 to 24 months behind; figures are dated accordingly.

    Possibly out of date. A more recent filing (FY2025) is on record but names no grant recipient in the published copy, so the figures above are from FY2020, the most recent year this funder’s grantee list reached the public record.

    Source object · view filing

    Play a game based on Kim and Don Richards Family’s filings →

    More from the funding graph

    The unnamed billions
    grants reported with no recipient in the public record
    The regranting layer
    51% of grant dollars land in the regranting layer
    The DAF merry-go-round
    $9.7B circulates between donor-advised funds
    The endowment market
    who holds foundation money, and what just moved
    The camps
    funders cluster by geography, not ideology
    By state
    where grant money is based, and what stays home